3 HN users recommended this talk3 months2017–2018score 3
Years with an HN recommendation, 2007–2026
HN points to it as a technical talk from a chip designer on why AI hardware should put memory close to compute and use async data transfers.
Simon Knowles, co-founder and CTO of Graphcore, talks about "intelligence processors", chips designed specifically for machine learning. The talk was given at the RAAIS 2017 summit and covers Graphcore's architecture.
“Here's a nice technical talk from Graphcore's CTO about that” (HN, 2017)
Interesting approach, but very far off. I prefer GraphCore as a promising new lead in AI hardware. Moving computation close in with memory, and making data transfers async will speed up DL. [this video]
Graphcore's approach of memory near compute and async transfers.
Indeed, and that's why there are a couple of startups working on new chips and why Google has the TPU. Here's a nice technical talk from Graphcore's CTO about that [this video]
Technical talk from Graphcore's CTO on new AI chips.
I went to a talk from the CTO of Graphcore ( [link] ) on Monday. They are designing chips targeted at machine learning. As I understood it, their architecture comprises - lots of "tiles" - small processing cores with collocated memory (essentially DSPs) - very high bandwidth (90TB/s!) switching fabric to move data between tiles - "Bulk Synchronous Parallel" operation, meaning that the tiles do their work and then the switching fabric moves the data, and then we repeat. The key challenge he pointed to was power - both in terms of getting energy in (modern CPUs/GPUs take similar current to your car starter motor!) and also getting the heat out. Logic gates take a lot more power than RAM, so he argued that collocating small chunks of RAM right next to your processing core was much better from a power perspective (meaning you could then pack yet more into your chip) as well as obviously being better from a performance perspective. [this video] isn't quite the presentation I saw, but it has quite a lot of overlap. Hope that helps!
Overlaps heavily with a talk on Graphcore's tile architecture and power.
Video list and Hacker News comment labels from HackerTube (prompted by @karpathy), released under ODC-By 1.0, built on the open-index/hacker-news archive. Hacker News data is provided by Y Combinator; comments remain the work of their authors. Video titles, channel names and thumbnails belong to their creators and are shown via YouTube. HackerTube Watch is an unofficial edition. Data export of 2026-10-31.
Plays via YouTube's privacy-enhanced embed
3 Hacker News comments
From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.
Read more